Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data. Top biostatisticians from academia, biopharmaceutical industries, and government agencies discuss how these advances are impacting clinical trials and biomedical research.Divid
Introduction and Overview: Overview of Recent Developments for Interval-Censored Data. A Review of Various Models for Interval-Censored Data. Methodology: Current Status Data in the Twenty-First Century. Regression Analysis for Current Status Data. Statistical Analysis of Dependent Current Status Data. Bayesian Semiparametric Regression Analysis of Interval-Censored Data with Monotone Splines. Bayesian Inference of Interval-Censored Survival Data. Targeted Minimum Loss-Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data. Consistent Variance Estimation in Interval-Censored Data. Applications and Related Software: Bias Assessment in Progression-Free Survival Analysis. Bias and Its Remedy in Interval-Censored Time-to-Event Applications. Adaptive Decision Making Based on Interval-Censored Data in a Clinical Trial to Optimize Rapid Treatment of Stroke. Practical Issues on Using Weighted Logrank Tests. glrt- New R Package for Analyzing Interval-Censored Survival Data. Index.